Layout 6 ANNALS OF GEOPHYSICS, 61,2, SE220, 2018; doi: 10.4401/ag-7705 1 “SEISMIC RISK EVALUATION FOR THE EMERGENCY MANAGEMENT„ Francesco Castelli1, Valentina Lentini2,*, Antonio Ferraro3, Salvatore Grasso4 1 PhD, Full Professor of Geotechnical Engineering, Faculty of Engineering and Architecture, University of Enna Kore, Enna, Italy 2 PhD, Assistant Professor of Geotechnical Engineering, Faculty of Engineering and Architecture, University of Enna Kore, Enna, Italy 3 PhD, Department of Civil Engineering and Architecture, University of Catania, Catania, Italy 4 PhD, Assistant Professor, Department of Civil Engineering and Architecture, University of Catania, Catania, Italy 1. INTRODUCTION In a high seismic hazard country, as Italy, with urban areas characterized by significant level of seismic vul- nerability, the seismic zonation, monitoring local net- works and earthquake early warning system, may allow the prevention and mitigation of the earthquakes effects [Castelli et al., 2013, 2016a, b, c; Castelli and Maugeri, 2008, 2013; Grasso et al., 2016; Grasso and Maugeri, 2014; Ferraro et al., 2016; Monaco et al. 2011]. Some recent examples of strong earthquakes in Italy include the central Italy earthquake of 24th August 2016, the L’Aquila earthquake of the 6th April 2009, the Emilia Romagna earthquake of the 29th May 2012, the St. Lucia earthquake of the 13th December 1990 occurred in the South Eastern of the Sicily. In particular, two ma- jor seismic areas there are in the South Eastern Sicily: the first along the Ionian coast (earthquakes of magni- tude M > 7.0) and the second in the hinterland area (earthquakes of magnitude lower than 5.5). These nor- mal faults were in the past sources of earthquakes with M up to 7.4 such as the 1169, 1693, 1818 and 1908 events. The seismic history of southeastern Sicily is characterized by several intense events, which, over the Article history Receveid May 26, 2017; accepted December 4, 2017. Subject classification: Seismic risk; Web-GIS platform; Monitoring. ABSTRACT The recent advances in cloud computing have opened new opportunities in emergency management issues due to earthquakes. In this context, Geographic Information System (GIS) based solutions have been recently investigated, with the aim of the prevention and the reduction of seismic risk. The paper focuses on the results of the research project PRISMA - cloud PlatfoRms for Interoperable SMArt Government in which an innovative open source GIS system, based on the knowledge in the field of dynamic characterization of soil has been developed in order to assess the local seismic hazard and the seismic zonation of the Enna area in the south of Italy. The paper describes how the application of prospecting and surveying techniques allowed a decisive improvement in the geological knowledge of the area, contributing to define the subsoil model for the purposes of seismic microzonation. The seismic geotechnical char- acterization has been performed with laboratory tests including the resonant column and cyclic torsional shear test on undisturbed sam- ples. The interpretation of geophysical and geotechnical data and their correlation with geological units are presented as microzonatic map. Finally, a wireless sensor network has been used for structural monitoring at the aim to highlight the significant benefits when the time available for access is limited, by representing an effective way of managing risks. All the data relating to the monitoring of the buildings and to the geological and geotechnical characterization are available on the web GIS platform, representing an important tool for the prevention and reduction of the seismic risk. centuries, caused severe damages and, sometimes, razed entire settlements [Barbano et al., 2014; Pappalardo et al., 2016]. Some of these events generated also destruc- tive tsunamis along the Sicilian Ionian coast (Figure 1). Earthquakes in Sicily are often among the main causes of land-slides, with particular reference to rock- falls. Such phenomena represent, in turn, a further risk for population and for structures and infrastructures [Pappalardo et al., 2014; Pappalardo and Mineo, 2015]. While these sudden disasters result in deaths, injuries, and homeless people, a quick response from the corre- sponding governments may include different techniques for post-disaster recovery. One big challenge that arises with disasters is that the telecommunication services (e.g., cellular networks, third generation, long term evo- lution services and internet infrastructures) usually be- come interrupted or overwhelmed. This congestion can be, particularly, noticed immediately after the disaster because the inhabitants of the affected area might want to, at the same time, communicate with the rest of the world. In order to deal with this challenge, the topic of designing an efficient disaster resilient network has re- cently gained much interest. As a consequence, re- searchers have diverted attention toward an alternate technology, namely the wireless mesh networks (WMNs), in order to construct disaster zone networks [Liu et al., 2010, 2012; Ngo et al., 2013; Wishart et al., 2008]. Recent advances in the development of Wireless Sensor Networks [Asplund and Nadjm-Tehrani, 2009] reveal a new paradigm for monitoring structures and infrastructure health [Shibata et al., 2009; Ishizu et al., 2011] and en- vironmental conditions [Fouda et al., 2012] owing to the availability of low powered millimeter-scale CPUs, highly integrated wireless transceiver circuits and var- ious miniature sensors. The paper focuses on the results of the research pro- ject PRISMA - cloud PlatfoRms for Interoperable SMArt Government in which a web-GIS platform, based on the knowledge in the field of dynamic characterization of soil and structural monitoring has been developed with the aim to provide the seismic zonation of the Enna area. Experimental and research activities have been per- formed through the active involvement of the Depart- ment of Civil Protection. The activities regard: i) geological and geotechnical characterization of the soil through in situ and laboratory test; CASTELLI ET AL. 2 FIGURE 1. Map of seismotectonic features of South-Eastern Sicily, with indication of 1693 and 1908 historical tsunamis. ii) wireless networks for monitoring strategic struc- tures; iii) collection of experimental data and their pro- cessing through GIS; iv) implementation of data [Castelli et al., 2015, 2016d, 2017; Castelli and Lentini, 2010, 2012; Maugeri et al., 2013] on an open cloud platform. Its architecture consists in a geospatial database sys- tem, a local GIS application for analyzing and modeling the seismic event and its impacts, a web-GIS module for sharing the geo-information among the public and pri- vate stakeholders and emergency managers involved in disaster impact assessment and response management. With this aim, data available by previous studies and in- vestigations, as well as, those deduced by the studies car- ried out within the Project PRISMA, have been organized in a database and geo-referenced. A set of data and in- formation needed for the evaluation of the seismic re- sponse are available on the web by the GIS platform, rep- resenting an important tool for the prevention and reduction of the seismic risk. The data derived by geotechnical investigations have identified different soil types within the studied area and the geophysical surveys have provided information on the values of the shear wave velocity VS in the different lay- ers and on the position of the bedrock. The results of res- onant column, torsional shear and cyclic triaxial tests have provided the dynamic characterization of the subsoil and the normalized shear modulus G/G0-γ and damping ratio D-γ versus strain curves for an accurate seismic response of soil, taking into account the non-linear behavior. 2. RISK PERCEPTION The analysis, assessment and mitigation of seismic risk, as well as developing smart technologies in support of these activities, must be accompanied by a careful study of the human factors involved in these processes. The ac- tive and aware involvement of population is necessary condition in order to achieve any successful intervention. In particular, analyzing perception of seismic risk by population, the trust among citizens and information or interventions implemented by institutions appear to be the key-issue. At the same time, Institutions must infuse trust in the population by policies activated to prevent and mitigate seismic emergencies. These considerations are not needed for an effective introduction of smart tech- nologies aimed at granting safety in an area: technolog- ical systems for alerting properly work only if citizens perceive them as reliable and useful. In this context, the use of systems for the diagnostics of the subsoil, damage assessment, and monitoring [Castelli and Lentini, 2016] of urban areas and infrastructure, is an option with signifi- cant social and economic implications in terms of better ability to manage emergency situations. The emergency management presents many criticali- ties due to various factors, like the human factor (reaction of panic, high number of victims, possible obstacles to the rescues), the environmental characteristics (presence of es- cape ways, extreme weather conditions, easy way or not to reach the interested area) and the coordination of the intervention itself (different agencies may use different procedures or may even evaluate the same situation in dif- ferent ways, thus disagreeing on the kind of intervention). Models and simulations of risk prevention and emer- gency alert have to take into account many risk factors, with different activation thresholds, and various ty- pologies of reaction for all the stakeholders. This requires not only the trust of citizens towards institutions (that is, their trust in the structure of prevention) but also the trust of institutions in citizens (as sources of informa- tion and as responsible agents in preventing to catas- trophes). However, trust attitude in the context of nat- ural catastrophes is complicated by a variety of factors: the number, diversity and complexity of relevant actors, the actions and interactions that each of them is able to implement, often without any coordination. A compre- hensive analysis of all these factors, as well as their in- teractions, allows to define and elaborate prevention rules with a high level of effectiveness. For all these rea- sons, success of intervention strategies during a natu- ral catastrophe relies heavily on distributed delegation actions towards actors capable of guaranteeing full trustworthiness, based on their well-tested and widely acknowledged expertise. 3. ANALYSIS, ASSESSMENT AND MITIGATION OF SEISMIC RISK IN SICILY Seismic zonation, monitoring local networks and alert systems may allow the promotion of appropriate policies for the prevention and mitigation of the earth- quakes effects, especially in a region with high seismic risk, as Sicily, and with an urban area characterized by high levels of seismic vulnerability. However, for the re- duction of seismic risk, the development of innovative experimental activities that enable the advancement of knowledge in the field of seismic geotechnical hazard as- sessment of sites and of the vulnerability of infrastruc- ture and civil and industrial facilities is necessary. Geo- logical and geotechnical aspects related to seismic prevention are particularly topical in Italy also in rela- 3 SEISMIC RISK MANAGEMENT tion to the effects caused by the recent earthquakes in the city of L’Aquila [Monaco et al., 2013; Santucci de Mag- istris et al., 2013), in the Emilia region [Facciorusso et al., 2016] and in the central Italy. In the past, the study of these problems was often limited to the geotechnical characterization of the sites and to the analysis of phe- nomena such as, subsidence or local seismic amplifica- tion, not reaching consistent suggestions about the pos- sibility to realize soil remediation to ensure the structures preservation. In contrast, the structural remediation is of- ten separated from the geotechnical characterization of the sites, the geotechnical modeling of the soil founda- tion and the actions for the improvement of the foun- dations. To overcome the limits of these approaches, the research activity will aim the analysis of the phenomena regarding the soil in order to evaluate the influence that they exert on the seismic vulnerability of buildings and systems to secure the achievement of seismic improve- ment. These goals can be achieved through an innova- tive experimentation in the field of evaluation of soil, structures and infrastructure behavior subjected to seis- mic loads. Therefore, the establishment of a monitoring network of seismic action for the acquisition of site data and the comparison with seismic amplification factors re- quired by national and international regulations and the procedures for the analysis of the seismic response [Cavallaro et al., 2006, 2008, 2012, 2013a, 2013b] in the case of difficult soil condition is expected. For more realistic assessment of the seismic hazard of a test site, it is necessary in addition to geological sur- veys, to take into account the historical and instrumen- tal seismicity of the area around the test site in order to better constrain the degree of regional seismicity. The aim of research activity is to realize a platform open cloud, based on the implementation of smart systems for mon- itoring characteristics of the environment. The data available on the platform allow the construction of seis- mic damage scenarios, the verification of the structural resistance of strategic buildings and the assessment of seismic vulnerability of the urban area, the verification of the practicability of the road system. 4. TEST SITE The testing activities was taken place in Sicily, with particular reference to the municipality of Enna, in col- laboration with the Regional Department of Civil Pro- tection and the Regional Province of Enna. Several prospecting and surveying techniques (geo- logical surveys, down-hole, MASW, HVSR) and labora- tory test for the static and dynamic characterization have been performed, allowing a decisive improvement in the geological and geotechnical knowledge of the area. For the purpose of seismic vulnerability assessment all buildings and houses of Enna have been classified by identifying the construction material (masonry or rein- forced concrete), the construction period, the number of floors, the surface in m2 and the number of inhabitants (Table 1,2). Furthermore, two typical buildings (Figure 2) of the constructed reality were chosen: reinforced con- crete and masonry buildings because these structural kinds represent over 90% of the built in Italy on the ba- sis of the results of ISTAT census [2011]. A set of spectrum compatible synthetic accelor- agrams for which was fixed a duration of 15 seconds have been generated. For each return period and for each generated signal a non-linear dynamic analysis with a FEM calculation code has been performed. Then for each return period, the probability of exceeding of each limit state has been evaluated and, consequently the fragility curves of the buildings. The synthetic ac- celerograms have been generated using the software REXEL-DISP [Smerzini et al., 2013] that allows to select suites of natural accelerograms compatible with dis- placement spectra of NTC’08. Records contained in REXEL-DISP are those of: Selected Input Motions for Displacement-Based Assessment and Design (SIMBAD). Figure 3 shows the acceleration spectra correspond- ing to the synthetic accelerograms generated for the sites in which is located the Duca D’Aosta School and the building of the Province of Enna respectively for a re- turn period equal to 475 years. In Figure 3 the red line is the average spectrum according to the Italian Tech- nical Regulations on the Constructions. The fragility curves have been re-calculated using natural accelerograms, selected in the strong-motion databank [Giardini et al., 2013]. The acceleration re- sponse spectra on rock and at ground surface, computed for the seven accelerograms selected, are shown in Fig- ure 4 in which xa and ya are the waveform identifica- tion code of the acceloragrams. 5. SENSOR NETWORK Earthquake Early Warning System (EEWS) are a rather recent development in seismology that allows to issue warnings to a site with a short lead-time about the im- pending arrival of the largest strong ground motion from an earthquake after the first wave arrivals have been de- tected nearer to the source by adequate sensors. Although the time interval between the warning and the arrival of the strong ground motion may be only of some minutes CASTELLI ET AL. 4 or seconds it allows for some important security measures to be taken to secure life and property. Among the activities performed in the context of re- search project there are: monitoring of strategic buildings, identification of the seismic input, definition of fragility curves by means of non-linear FEM analysis, collecting data for web-GIS platform. At this aim the two chosen buildings were instrumented for the structural monitoring. In particular, for the building of the Province of Enna, ul- trasonic measurements and dynamic identification tests were performed. The dynamic identification tests were car- ried out using triaxial velocimeters with sensitivity of 400 V/m/sec according to two different configurations: the first for the characterization of the tower and the second for the identification of the periods of the remaining part of the structure. Nine velocimeters for the real-time struc- tural health monitoring (Figure 5) and 4 velocimeters for the tower (Figure 6) were placed respectively. The recorded data regard the response of the structure to the natural ac- tions such as ambient noise, wind, earthquake, etc. At the acquisition of the signals is followed the step of processing of the data. In particular, through the pro- cessing of the data in the frequency domain of some parts of the acquired signals, the fundamental period of the structure has been evaluated. The performed recordings have permit the identification of probable frequencies and natural vibration modes of the structure equal to 4.125 Hz (0.24sec), 3.625 Hz (0.27sec) and 12.5 Hz (0.08sec). The recordings on the tower have provided a value of fre- quency along x direction equal to 3 Hz (0.33sec) and along the Y direction equal to 3.5 Hz (0.28sec). On the ba- sis of the experimental monitoring and the study per- formed an Earthquake Early Warning System could be implemented in a web GIS platform on the basis of ob- tained results in terms of natural frequencies. 6. GEOTECHINICAL CHARACTERIZATION OF THE TEST SITE To manage the seismic risk and to allow for effective and efficient management of communications during the alert and emergency phases, a desktop application for Local Authorities has been realized. The application consists of an advanced system which combines the ex- perimental data provided by structural monitoring and 5 SEISMIC RISK MANAGEMENT Code Meaning Material 1 masonry 2 Reinforced concrete pilotis 3 Reinforced concrete no pilotis 4 other Floor 1, 2, 3, 4, 5 if material =1 1, 2, 3, 4, 5, 6, 7, 8 if material = 2, 3, 4 Period 1 < 1919 2 1919 - 1945 3 1946 - 1961 4 1962 - 1971 5 1972 - 1981 6 1982 - 1991 7 > 1991 no. houses Number of houses within the group identi- fied with material, floor and period no. buildings Number of buildings within the group identified with material, floor and period surface (m2) Surface in m2 within the group identified with material, floor and period no. inhabitants Number of inhabitants within the group identified with material, floor and period TABLE 1. Code and meaning for buildings census. CASTELLI ET AL. 6 Material Floor Period no. houses no. buildings Surface m2 no. inhabitants 1 3 2 27 12 2860 55 1 3 3 42 26 4246 94 1 3 4 11 6 1166 13 1 3 5 1 1 140 3 1 4 2 3 1 392 6 2 1 2 8 3 730 10 2 1 3 5 5 471 16 2 1 4 51 33 5134 125 2 1 5 34 25 3907 78 2 1 6 35 31 4097 78 2 1 7 15 15 1822 32 2 2 2 3 3 293 4 2 2 3 8 5 894 11 2 2 4 23 15 2329 48 2 2 5 63 48 7006 155 2 2 6 40 27 5198 98 2 2 7 16 12 1763 38 2 3 4 34 7 3148 87 2 3 5 4 3 560 6 2 3 6 23 6 2601 45 2 3 7 2 1 176 5 2 4 2 1 1 150 2 2 4 4 45 6 3730 103 2 4 5 17 2 1496 32 2 5 4 7 1 537 19 2 7 4 46 4 3370 76 3 1 4 7 4 1015 14 3 1 5 8 5 720 16 3 1 6 7 5 1067 27 3 1 7 12 9 1337 38 3 2 2 10 6 755 24 3 2 3 36 15 3766 81 3 2 4 55 32 5197 140 3 2 5 31 19 3753 86 3 2 6 55 21 5569 157 3 2 7 95 54 11007 284 3 3 2 8 2 639 18 3 3 4 17 4 1647 43 3 3 5 74 9 6516 204 3 3 6 6 1 504 9 3 3 7 28 7 2801 82 3 4 4 2 1 180 3 3 4 5 19 2 1654 45 3 5 4 43 2 2885 87 3 5 5 198 8 13234 554 3 6 5 54 1 4303 149 4 1 1 2 1 200 6 4 1 2 2 2 260 4 4 1 3 5 4 578 12 4 1 4 6 6 459 7 4 1 5 3 3 303 6 4 1 6 1 1 80 4 4 2 1 5 4 456 8 4 2 2 7 5 764 16 4 2 3 44 39 3720 72 4 2 4 36 32 3232 64 4 2 5 6 5 444 8 4 2 6 2 1 205 6 4 2 7 2 2 292 5 4 3 2 10 6 1233 17 4 3 3 15 11 1812 33 4 3 4 22 14 1822 53 4 3 5 7 5 871 17 4 4 4 4 1 275 10 TABLE 2. Buildings census. the available data derived from geotechnical investiga- tion geo-referenced through the Geographical Infor- mation System (GIS) with the probable impacts on the territory, providing a forecast of the seismic risk. 7 SEISMIC RISK MANAGEMENT FIGURE 2. Reinforced concrete building: Duca D’Aosta School (a); masonry building: Palace of the Regional Province of Enna (b). (a) (b) FIGURE 3. Response spectra for synthetic accelerograms for the sites of the Duca D’Aosta school (a), and of the Province of Enna building (b). a) (b) At this aim a detailed survey, comprising in situ and laboratory tests have been performed and at the same time the data available related to geotechnical proper- ties for several municipalities of the Province of Enna have been collected. The collection and analysis of exiting data from pre- vious geotechnical investigations was the first step in planning the site investigation program. For several municipalities of the Province of Enna are available Down - Hole (DH), Multichannel Analysis of Surface Wave (MASW), Horizontal to Vertical Spectral Ratio (HVSR), Refraction Microtremor (REMI) and electrical to- mography tests (Table 3). A preliminary selection of re- sults of in situ tests have been collected throughout the past years by the public administrations. For an accurate dynamic subsoil characterization of such sites, surface wave tests were planned in all of them. Down - Hole tests were carried out only in sites with apparently deep seismic bedrock. In the paper, the results of geotechnical soil charac- terization exclusively of the municipality of Enna are re- ported. The geotechnical parameters of the soil founda- tion have been derived from the boreholes down to a depth of 30.0 m, equipped to perform Down Hole Tests (DH) to evaluate the propagation velocity of seismic compression VP and shear VS waves or with piezome- ters in order to monitor the water level. To determine the propagation velocity of the body CASTELLI ET AL. 8 FIGURE 4. Response spectra of accelerograms on rock (a) and at ground surface (b). a) (b) FIGURE 5. Structural monitoring system for the ground level (a), the first level (b) the second level (c) of the Province of Enna building. a) (b) (c) waves DH tests has been carried out. The velocities profiles VP and VS shows a progressive increase with depth, within a range of about 120 and 400 m/sec for shear waves and about 200 and 2200 for compression waves (Table 4). In the investigated site, n.40 multi- receiver surface wave (MASW) tests were also per- formed (Figure 7). The Surface Wave Method is used for evaluating shear wave velocity profile. It is based on the dispersion of sur- face waves in heterogeneous media: the velocity of each harmonic component of the surface wave depends on the properties of the medium affected by the wave propaga- tion and its penetration depth is proportional to the wave- length. Dispersion curves (velocity versus waves fre- quency) can be extracted from field data, using processing technique. The shear wave velocity profile can be in- ferred by solving an inverse problem. The MASW tests were performed using active acqui- sition technique. The Figures 8 and 9 report a set of trial profiles, including the best-fitting profile, and the dis- persion curve respectively. A first validation of the MASW shear wave velocity profiles was possible by means of the DH tests avail- able in the test site. The shear wave velocity profiles ob- tained from the DH and MASW tests are compared in Figure 10 for all data available (a) in the city of Enna and for the C.da S. Panasia area. It can be observed that DH and MASW test results are very in good agreement. Within the experimental activities of PRISMA n.80 single station measurements of microtremors have been performed in the city of Enna (Table 5). Indeed, the experimental horizontal to vertical spectral ratio (HVSR) of ambient noise provide a rea- 9 SEISMIC RISK MANAGEMENT FIGURE 6. Structural monitoring system for the tower of the Province of Enna building. sonable estimate of the fundamental natural frequency of the site. The results of in situ test were used to represent a the- matic map in which are reported for Enna site the values of the parameter VS,30, computed according to the Italian Technical Regulations on the Constructions (Figure 11). 6.1 GEOTECHNICAL PROPERTIES FROM ROUTINE LABORATORY TESTS The geological survey [Pappalardo and Rapisarda, 2016] shows that foundation soils include in the first meter fine sand and/or sandy silt and at a major depth blue-grey silt clay. The geotechnical characterization of the soil of the test site is carried out by routine laboratory tests. The values of the main index properties and the percentage of grain size distribution are summarized in Table 6. Most of the samples are coarse-grained soils, classifiable as sandy silts to silt sands, showing a lower percentage of clayey material. According to the particle size distribution, the tested samples can be classified into two main groups on the basis of clay fraction: lower than 30% and higher than 30%. Phys- ical parameters, in terms of water content wn, soil unit weight γ, plasticity index PI, were derived from stan- dard classification tests performed on the samples re- trieved by geotechnical survey. CASTELLI ET AL. 10 Test Enna Agira Aidone Assoro Barrafranca DH 6 - - - - MASW 11 10 1 4 7 REMI 2 1 2 1 2 HVSR 2 1 1 1 7 Electrical Tomography - - 1 3 - Test Calascibetta Catenanuova Centuripe Cerami Gagliano C.to DH 1 - - - - MASW 2 2 2 2 2 REMI 1 1 1 1 1 HVSR 1 1 1 1 1 Electrical Tomography - - - - - Test Leonforte Nicosia Nissoria Piazza Armerina Pietraperzia DH - 1 - - - MASW 1 2 1 4 1 REMI 3 1 2 1 1 HVSR 1 1 1 3 1 Electrical Tomography 1 - - - - Test Regalbuto Sperlinga Troina Valguarnera Caropepe Villarosa DH - - - - - MASW 5 1 1 2 1 REMI 1 1 2 1 1 HVSR 1 1 1 1 1 Electrical Tomography - - - - - Soil Vs (m/s) Silty sand 500¸700 calcarenites 1200 Clay marnes 300¸400 Grey clay 200¸300 Chalky clay 700¸800 Chalk 1800¸2200 TABLE 3. Summary of site tests available for the municipalities of the Province of Enna. TABLE 4. Shear waves velocity for lithological units in the Enna area. 6.2 STIFFNESS AND DAMPING FROM LABORATORY TESTS Soil non-linear behavior was analyzed by means of fixed-free Resonant Column/Torsional Shear (RC-CTS) devices. The specimens were consolidated isotropically to the estimated in situ stress. At the end of the consol- idation stage, the cyclic and/or dynamic tests were per- formed with increasing shear load levels, to investigate the behavior of the soils for shear strains ranging be- tween 0.0001% and 1%. As usual, the tests were inter- preted in terms of linear equivalent parameters, i.e. shear modulus G and damping ratio D. To evaluate the dynamic properties of the soil and in particular to determine the degradation law of shear modulus G and the increase law of damping ratio D sev- eral tests were performed with the Resonant Column/Cyclic Torsional Shear apparatus. In RC tests, sinusoidal torsional forces are generally applied at high frequencies, so as to reach the resonance conditions. For low and medium levels of deformation 11 SEISMIC RISK MANAGEMENT FIGURE 7. Geological map of Enna with location of the HVSR tests and MASW tests. torsional forces are generally applied at frequencies be- tween 1 and 100 Hz. At higher levels of deformation, the frequency of torsional forces ranges from 0.01 to 1 Hz. RC and CTS tests have been carried out on cylinder soil samples with 50 mm of diameter and 100 mm of length, by the use of electromagnetic actuators, in order to perform both RC and CTS tests with the same equipment on the same sample. Figure 12 shows the experimental results obtained from the resonant column and cyclic torsional shear test in terms of normalized shear modulus G/G0 (Figure 12a) and damping ratio D (Figure 12b) versus shear strain γ. Experimental results have been compared in CASTELLI ET AL. 12 FIGURE 8. Best - fitting profile. FIGURE 9. Dispersion curve. FIGURE 10. Enna site: comparison of shear wave velocity profiles obtained by MASW tests and Down-Hole tests. 13 SEISMIC RISK MANAGEMENT Station f0 A0 f1 A1 f2 A2 Bedrock depth (m) TR1 7 TR2 4,69 2,11 7 TR3 7 TR4 22 TR5 7 TR6 10,72 1,7 10 TR7 31,72 6,25 9,8 TR8 7 TR9 2,5 2,8 4,2 2,1 24 2,7 32,2 TR10 7,3 TR11 15 TR12 15 TR13 31 2 7 TR14 5,5 2 19 TR15 12,95 2,2 16 TR16 2,5 2,71 3,5 2 26 TR17 5 2,1 37,4 TR18 35 2 6,5 TR19 5 2 7,92 2,9 7,7 TR20 7,2 TR21 1,23 2,3 28,6 TR22 3 2 4,52 2 17,9 TR23 5 2 26 TR24 0,53 1,8 19 TR25 16,72 1,73 7,7 TR26 16 TR27 27 3 7,7 TR28 0,44 3,5 5 2,8 20 TR29 20,63 2,2 8 TR30 20 TR31 2,8 3,5 20 TR32 18,5 TR33 7,2 6,8 17,2 TR34 4,2 2 5,2 2 18,4 TR35 2 2,3 76 TR36 19,83 4,2 21,7 TR37 1,28 2,5 50 TR38 5,94 2 18,5 TR39 14,38 2 12 CASTELLI ET AL. 14 TR40 5,77 2 12,1 TR41 0,92 3,68 22 TR42 1,7 2,3 24 3 50 TR43 2,66 4 50 TR44 2 2 12 2,9 66 TR45 4,63 4 19 2,1 42 TR46 20 2,2 38 2 15,5 TR47 3,4 2,2 35 2,5 15,5 TR48 3,7 3 15,5 TR49 6 2,2 48 TR50 1,55 1,83 15,5 TR51 2 4,25 26 2,9 26 TR52 1,39 2,35 2,5 2 42 TR53 3,09 2,68 58 TR54 2,2 3 31,09 3,6 44 TR55 2,2 3 4,63 3,2 40 TR56 2,3 2 50 TR57 2,81 3,32 7,2 2,7 42 TR58 50 TR59 1,3 2,6 4 2,5 15 3 35 TR60 2,6 2,8 42 TR61 4,5 3 41,3 TR62 1,5 2,6 4,02 3 17 2,2 27 TR63 25 TR64 1,6 2,5 2,8 2,6 42,4 TR65 23 TR66 0,66 2,4 25 TR67 3 2 40,1 TR68 2,02 3,6 55 TR69 2,81 1,8 50 TR70 1,52 4,8 10 2,2 24,7 TR71 2,19 2,4 20 TR72 2,61 3 33 2,8 46,44 TR73 47,7 TR74 22,03 1,6 27,3 TR75 1,95 1,5 25 TR76 2,5 2 20 3,8 22 TR77 22 TR78 2,3 2,5 4 3,2 20,2 TR79 48 TR80 3,75 3,4 22 3 48 TABLE 5. Single station measurements of microtremors. 15 SEISMIC RISK MANAGEMENT FIGURE 11. VS,30 map for Enna site. Figure 13 with the curves proposed by Darendeli [2001] for soils with plasticity index equal to 30% and for mean effective confining pressure σ’0 equal to 100 kPa for soils tested in the range 75-150 kPa. The comparison among the tested specimens re- flected their differences in physical properties, con- firming that clay fraction and plasticity index are key parameters to represent soil non-linearity. The curves relevant to silty-low plasticity soils define a range of lin- ear behavior not exceeding a threshold strain level of the order of 0.005% beyond which the decay of stiffness and the increase of damping are quite pronounced. The CASTELLI ET AL. 16 Site Sample Depth (m) Clay (%) Silt (%) Sand (%) γ (kN/m3) wn (%) Ip (%) eo C.da Santa Panasia S1/C2 6,00 39,36 41,31 19,32 20,21 19,90 - - S2/C1 2,00 12,34 14,46 71,59 19,26 19,33 - - S2/C2 5,50 30,73 39,50 25,61 19,66 31,26 33,47 0,731 S2/C4 15,5 35,33 44,94 19,74 20,01 20,02 42,12 0,581 S3/C1 1,50 11,75 17,97 64,41 19,01 20,99 11,58 - S3/C2 4,00 5,39 2,25 89,38 19,67 13,76 - 0,584 S3/C3 8,00 20,60 27,07 52,29 20,26 20,27 8,58 0,569 S3/C4 15,3 28,50 48,71 22,79 20,05 22,74 48,84 0,608 C.da S. Anna S1/C2 8,00 10,15 30,01 46,11 19,27 24,74 14,80 - S1/C3 18,0 25,13 53,54 21,27 19,88 31,86 36,39 - S2/C1 3,00 23,35 43,79 25,63 20,02 21,97 19,97 - S2/C3 13,2 37,45 51,80 10,72 20,52 22,50 47,44 0,495 S3/C2 5,70 26,24 34,80 36,44 19,25 28,18 22,79 - TABLE 6. Geotechnical properties derived by laboratory tests. FIGURE 12. Normalized shear modulus (a) and damping ratio (b) vs shear strain from RC and CTS tests. a) (b) curves relevant to clayey-high plasticity soils are char- acterized by higher values of the linear threshold of the order of 0.01%, showing a less evident reduction of stiff- ness and lower damping values in the non-linear range. 7. SITE RESPONSE ANALYSIS The study of topographic factors, with the informa- tion related to the surface morphology and to the me- chanical properties of soil is fundamental for a reliable seismic response analysis. The paper proposes results from seismic analysis performed in 1D and 2D field based on geological, geotechnical and geophysical stud- ies with reference to the Enna area. The 1D numerical simulations were performed through the STRATA [Kottke and Rathje, 2008] and EERA [Bardet et al., 2000]. codes; the seismic bedrock depth was assumed at 30 m. The input motion (Figure 14) is the St. Lucia earthquake (13 December 1990) recorded to Sortino (SR). The results obtained from the two numerical codes in terms of peck ground accelera- tion (PGA) versus depth are presented in Figure 15, showing a good agreement. The maximum value of PGA obtained at the surface is equal to 0.203 g. When the section is characterized by a ratio between the depth and the distance from the edges greater than 2, then the 1D analysis may give unreliable results [Lanzo and Silvestri, 1999]. For this reason, topographic effects on the hill of Enna have been studied through the QUAKE/W [Krahn, 2004] computer code. The 2D simulations have been performed considering a cross section (Figure 16) that covers 2060 m in length and 280 m in elevation; the numerical method used is the finite element implemented is QUAKE/W. Rectan- gular shaped elements have been used in the finite ele- ment domain discretization. The boundary conditions applied to lateral boundaries are nodal zero vertical displacements and the boundary condition at the bottom of the model are nodal zero vertical and horizontal dis- placements (Figure 17). Finally, the input time history ac- celeration relating to St. Lucia earthquake (13 December 17 SEISMIC RISK MANAGEMENT FIGURE 13. Normalized shear modulus (a) and damping ratio (b) vs shear strain from RC and CTS tests compared with lit- erature curve by Darendeli (2001) for σ’0 equal to 100 kPa. a) (b) FIGURE 14. Input motion recorded to Sortino (SR) station during St. Lucia earthquake (13th December 1990). FIGURE 15. Peack ground acceleration versus depth for the bedrock depth at 30 m. 1990) (SR) has been applied at the bottom of the mesh. The analyses were performed based on the soil properties derived from field investigation and laboratory tests. For the purpose of this numerical study carried out along the cross section of Enna, this seismic bedrock model seems to be the most representative, provided that the input motion is the 1999 St. Lucia earthquake recorded at Sortino and accurate geotechnical and ge- ological characterization of deep deposit is available. Figure 18 shows the values of the maximum accel- eration obtained by 1D (red line) and 2D (blue line) sim- ulations. It is possible to note that the value of PGA on the crest are greater than those on the edges. 8. SEISMIC MICROZONATION OF THE AREA The Seismic Microzonation is a cognitive tool aim- ing at the mitigation of seismic risk of an area. It should be conducted on the basis of the Guidelines for Seismic Microzonation that defines three levels of detail and the corresponding improvements of knowledge that should be carried out to achieve each one, depending also on the local hazard. Level 1 is an introductory level con- sisting of a collection of exiting data processed to de- fine the subsoil model and a Seismic Microzonation map in which the territory is qualitatively classified into ho- mogeneous microzones. Level 2 introduce the quantita- tive elements associated with the homogeneous zones, using additional investigations and a new Seismic Mi- crozonation map is produced. Level 3 contains insights on topics and/or on particular areas. All the considerations discussed above were inte- grated in a map of homogeneous microzones in seismic perspective (Figure 19) in which some areas were iden- tified as homogeneous on the basis of main parameters as: lithological and lithotecnical characteristics, depth of bedrock, geomorphological conditions, etc. The integration of geological, geophysical and geotechnical data allowed to distinguish n.29 zones characterized as stable zones but susceptible of local seismic amplification. In the same Figure 4 instable mi- crozones can be distinguished. 9. CONCLUDING REMARKS In the last years, strong earthquakes occurred in Italy have highlighted the ineffectiveness of prevention policies. To acquire a greater knowledge on the seismic risk affecting urban areas, geological and geotechnical characterization of the soil is the main step. Within this aim, smart technologies allow the management and sharing of complex information relating to the seismic vulnerability of exposed resources. The thematic maps are cognitive tools aiming at the mitigation of seismic risk of an area. The realization of a risk map is a com- plex task that involves the combination of data coming from different field of expertise, such as geology and geotechnical and structural engineering. The paper de- scribes how the application of prospecting and survey- ing techniques allowed a decisive improvement in the CASTELLI ET AL. 18 FIGURE 16. Cross section of Enna. FIGURE 17 2D Boundary condition of the model. FIGURE 18 Comparison between 1D and 2D PGA. geological knowledge of the test site, contributing to de- fine the subsoil model for the purposes of seismic mi- crozonation. The paper also reports the seismic geotech- nical characterization performed with laboratory tests including the resonant column and cyclic torsional shear test on undisturbed samples. The results are sum- marized in terms of variation of stiffness and damping with shear strain. Finally, wireless sensor for structural monitoring have been used, having significant benefits when the time available for access is often severely lim- ited and representing an effective way of managing risks once that an area of concern has been identified. 19 SEISMIC RISK MANAGEMENT FIGURE 19 Map of homogeneous microzones in seismic perspective for Enna area. REFERENCES Asplund M. and S. Nadjm-Tehrani (2009). A partition-tol- erant many cast algorithm for disaster area networks. 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